Ha-Thanh Nguyen
- Artificial Intelligence top 10%
- Political Science and International Relations top 10%
- Signal Processing
- Information Systems
- General Health Professions
- Co-authors
- Le-Minh NguyenYannick EstèveVu TranLaurent BesacierNatalia TomashenkoArie RotemBui Thi Tu QuyenLinh Cu Le
- Topics
- Topic Modeling (21 papers)Natural Language Processing Techniques (21 papers)Artificial Intelligence in Law (14 papers)
In The Last Decade
Ha-Thanh Nguyen
43 papers receiving 308 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 200
- Political Science and International Relations 67
- Signal Processing 33
- Information Systems 24
- General Health Professions 16
Countries citing papers authored by Ha-Thanh Nguyen
This map shows the geographic impact of Ha-Thanh Nguyen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ha-Thanh Nguyen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ha-Thanh Nguyen more than expected).
Fields of papers citing papers by Ha-Thanh Nguyen
This network shows the impact of papers produced by Ha-Thanh Nguyen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ha-Thanh Nguyen. The network helps show where Ha-Thanh Nguyen may publish in the future.
Co-authorship network of co-authors of Ha-Thanh Nguyen
This figure shows the co-authorship network connecting the top 25 collaborators of Ha-Thanh Nguyen. A scholar is included among the top collaborators of Ha-Thanh Nguyen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ha-Thanh Nguyen. Ha-Thanh Nguyen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 15 | |
| 9 | 34 | |
| 10 | How State-Of-The-Art Models Can Deal With Long-Form Question Answering | 1 |
| 11 | Latent Topic Refinement based on Distance Metric Learning and Semantics-assisted Non-negative Matrix Factorization | 1 |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 31 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 19 | |
| 20 | 4 |
About Ha-Thanh Nguyen
Ha-Thanh Nguyen is a scholar working on Geology, Artificial Intelligence and Political Science and International Relations, having authored 50 papers that have together received 318 indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (21 papers) and Artificial Intelligence in Law (14 papers). The work is most often cited by research in Artificial Intelligence (200 citations), Signal Processing (33 citations) and Political Science and International Relations (67 citations). Ha-Thanh Nguyen has collaborated with scholars based in Vietnam, Japan and France. Frequent co-authors include Le-Minh Nguyen, Yannick Estève, Vu Tran, Laurent Besacier, Natalia Tomashenko, Arie Rotem, Bui Thi Tu Quyen, Linh Cu Le, Cuong Pham and Từ Minh Phương. Their work appears in journals such as Expert Systems with Applications, International Journal of Epidemiology and Dalton Transactions.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.